Existing Models

Name Publication Year What? Relevancy Link
Computational (Neuro)phenomenology Model 2024 Uses a coupled classifier and generative deep neural network to simulate visual hallucinations. • It can generate "synthetic VHs" characteristic of different aetiologies, including psychedelics.
• It considers key dimensions like realism, dependence on sensory input, and complexity.
• It uses Deep Convolutional Neural Networks (DCNNs) and Deep Generator Networks (DGNs), which could be adapted for our LSD-specific model. https://doi.org/10.3389/fnhum.2023.1159821
Serotonin 2A (5-HT2A) Receptor Activation Model 2016 Directly relevant to LSD-induced hallucinations • It focuses on 5-HT2A receptor activation, crucial for LSD's effects.
• It suggests that 5-HT2A receptor activation increases neuronal excitability and alters visual-evoked cortical responses.
• This mechanism could be incorporated into our computational model to simulate LSD's effects on cortical activity. 10.3390/ijms17111953
Visual Cortex AlterationsandThalamocortical Interactions 2017 • LSD increases functional connectivity between the primary visual cortex (V1) and other brain regions.
• It alters spontaneous activity in retinotopically organized areas of V1 and V3, even with eyes closed.
• These changes correlate with ratings of elementary or complex hallucinations.
• LSD-induced changes in thalamocortical connectivity are linked to visual and auditory alterations.
• This could be incorporated into our model to account for the role of thalamic gating in hallucinations. 10.1038/npp.2017.86
Rebeus Model

Ideas